Using environmental DNA for sampling fish – is it the future?
Graeme Peirson 25th July 2018 What is eDNA? DNA that has been released by an organism into the environment in the form of mucus, skin, hair, faeces, urine, gametes etc. From live organisms and dead ones as they decompose eDNA degrades at varying rates according to the environment – may persist for 000’s years! Much shorter decay time in water – weeks only eDNA can be extracted from water without having to isolate the individual organism So why eDNA? Conventional capture methods: Labour-intensive Bulky equipment, costly to store & maintain Health & safety/biosecurity concerns Invasive / destructive (some methods) Limited effectiveness in some water types Hydroacoustics Information on size and abundance only, limited species ID Ineffective in many environments • Shallow, weedy, snaggy areas, marginal zones, benthic species The Process…..
Water sampled & filtered (>3 x 15 ml -2L samples)
Free-floating DNA (from sloughed skin cells faeces/urine, gametes, decaying matter) and microscopic taxa Next steps…
Filtration and Non – specific PCR Extract DNA DNA extraction
Blanks! Blanks!
Primers: Riaz et al. 2011, Kocher et al. 1989 Metabarcoding and species-specific approaches eDNA targeted approches: • Targeted detection • Species-specific primers • Standard or qPCR • Traditional Sequencing
=
eDNA metabarcoding: • Screen whole community • (Several) conserved primers • PCR • Next generation sequencing = Sequencing and bioinformatics
High Bioinformatics Final outputs Throughput Sequencing - Quality control - Site - Sample ID occupancy - Trimming - Data base matching
- Read counts per species So does it work?
Developing eDNA for sampling lake fish for Water Framework Directive – a collaborative approach Environment Agency Scottish Environmental Protection Agency, University of Hull (EVO), Centre for Ecology & Hydrology, Natural Resources Wales Natural England Food and Environment Research Agency Pilot study – Windermere 2015 • Three lakes in the UK Lake District • Windermere • Derwent Water • Bassenthwaite Lake • 2L water samples along boat transect at 1m, 5m & 20m depths, plus shore sampling.
• Two mitochondrial gene fragments (12S and Cyt b) Results
1
0.8
0.6
0.4 12S freq cytb freq
0.2 Proportion of sites present sites of Proportion
0
Eel Pike* Rudd Smelt Perch* Roach* Salmon Tench* Ruffe* Flounder Bullhead* Minnow* Sunbleak* Stone loach 3-spined SB Sea lamprey Arctic charr River lamprey Brown trout* Common carp* RainbowMudminnow* trout Common bream* Topmouth gudgeon* Results – Windermere – species detection Previously (ever) recorded species (16) 12S: 14 (88%) Cytb: 12 (75%) Gill netting survey 2014: 4 (25%) Species not previously recorded 12S: 6 species Cytb: 3 species Including carp, ruffe: maybe present ? also smelt, TMG, flounder, sunbleak – false positives? eDNA reflects species abundance
a) Windermere North Basin b) Windermere South Basin
PER 1.0 Spearman: rho=-0.835, P=5.713e-05 PER BTR ROA Spearman: rho=-0.766, P=0.00005 ROA 1.0 MIN BUL 3SS
0.8 BRE
PIK 0.8 BTR
PIK 0.6
0.6 EEL LOA CHA BUL 0.4
EEL LOA 0.4 SAL 3SS BRE MIN 0.2 0.2 TEN CHA SAL RUD Site Occupancy (12S) Site Occupancy RUD RLA SLA (12S) Site Occupancy TEN RLA SLA 0.0 0.0
5 10 15 5 10 15
Long term rank Long term rank
c) Bassenthwaite d) Derwent Water
RUF PIK BTR MIN 1.0 PER MIN PIK 1.0 PER SAL 0.8 RUF BTR 0.8 ROA EEL DAC
0.6 ROA 0.6
VEN EEL 0.4 0.4 0.2 0.2 Spearman: r=-0.556, P=0.120 Site Occupancy (12S) Site Occupancy Spearman: rho=-0.216, P=0.549 VEN (12S) Site Occupancy DAC 0.0 0.0
2 4 6 8 10 2 4 6 8
Long term rank Long term rank
e) Windermere North Basin f) Windermere South Basin 1.0 Spearman: rho=-0.721, P=0.002 PER Spearman: rho=-0.779, P=0.0004 PER 1.0
0.8 BRE 0.8 BTR ROA 0.6
BUL 0.6 MIN 3SS 0.4
ROA 0.4 BTR EEL PIK PIK EEL BRE BUL 0.2 CHA
0.2 LOA SAL MIN 3SS LOA CHA Site Occupancy (cytb) Site Occupancy TEN RUD RLA SLA (cytb) Site Occupancy TEN SAL RUD RLA SLA 0.0 0.0
5 10 15 5 10 15
Long term rank Long term rank
g) Bassenthwaite h) Derwent Water
Spearman: rho=-0.388, P=0.267 1.2 0.6 RUF BTR PER Spearman: rho=-0.372, P=0.323 1.0 0.5 PER
0.8 SAL 0.4 RUF PIK 0.6 0.3
PIK MIN BTR EEL 0.4 0.2
EEL MIN 0.2 0.1
Site Occupancy (cytb) Site Occupancy ROA DAC VEN (cytb) Site Occupancy ROA VEN DAC 0.0 0.0
2 4 6 8 10 2 4 6 8
Long term rank Long term rank eDNA reflects species ecology a) Read Count: 12S b) Read Count: cytb 30
1.0 1.0
) -3 25 0.8 0.8 20 South
0.6 150.6 basin
0.4 100.4
Proportion of Sequence Reads of Sequence Proportion Reads of Sequence Proportion 5
0.2 0.2 North Mean SRP in first 4 weeks (mg m (mg weeks 4 first in SRP Mean
0 basin
0.0 19450.0 1955 1965 1975 1985 1995 2005 South Basin North Basin South Basin North Basin a) Proportion ReadYear Count: 12S
c) Site Occupancy: 12S 1.0 d) Site Occupancy: cytb Legend 1.0 1.0 S. salar P. phoxinus 0.8 Oligotrophic
0.8 0.8 C. gobio association S. trutta S. alpinus
0.6 0.6 0.6 T. tinca S. erythrophthalmus Eutrophic R. rutilus 0.4 0.4 association A. anguilla 0.4 A. brama Proportion of Sites Occupied Proportion of Sites Occupied Proportion B. barbatula Sequence Reads Sequence 0.2 0.2 No E. lucius 0.2 association P. fluviatilis G. aculeatus 0.0 0.0 South Basin North Basin South Basin North Basin 0.0 North South
b) Proportion Read Count: cytb
1.0
0.8
0.6
0.4 Sequence Reads Sequence
0.2
0.0 North South Relationship with actual species relative abundance
New Lake species composition by number New Lake species composition by biomass
Carp F1 Crucian Carp F1 Crucian Bream Tench Roach x Bream Hybrid Bream Tench Roach x Bream Hybrid Rudd Perch Chub Rudd Perch Chub Barbel Wels Catfish Sterlet sp. Barbel Wels Catfish Sterlet sp. Grass Carp Roach Grass Carp Roach
New Lake species composition by read-count (unassigned removed)
Abramis_brama (common bream) Barbus_barbus (barbel) Blicca_bjoerkna (silver bream) Carassius_auratus (goldfish) Carassius_carassius (crucian carp) Ctenopharyngodon_idella (grass carp) Cyprinus_carpio (common carp) Hypophthalmichthys_molitrix (silver carp) Leuciscus_leuciscus (dace) Rutilus_rutilus (roach) Scardinius_erythrophthalmus (rudd) Squalius_cephalus (chub) Tinca_tinca (tench) Esox_lucius (pike) Gasterosteus_aculeatus (stickleback) Salmo_trutta (brown trout) Silurus_glanis (Wels catfish) Cyprinidae (cyprinids) Percidae (perch family) Application of thresholds to exclude false positives
So the simple answer to the question is yes, eDNA can give a realistic picture of the fish community in a water body Challenges Differentiation of some closely-related species False positives, false negatives Standardisation of protocols to enable comparability of results Using eDNA derived data in metrics which can be used for fisheries classification Using relative abundance derived by eDNA of known indicator species? Or: direct comparison of fish eDNA “signature” with other aspects of water body status? What about rivers?
Challenges posed by transport of eDNA down the river and from tributaries Is species x present here or further upstream? Work to understand transport and decay of eDNA in flowing water – Belgium, France and Austria – See Pont et al (2018) Consider river reaches rather than sites Good for looking at presence/absence of rare and cryptic species From Pont et al (2018) – river Rhone What an eDNA-based approach can do… Can be deployed in any aquatic environment Non-invasive Requires relatively little field-based manpower or equipment Relatively unselective Future looks bright! Extend use to flowing water Unit costs will fall as the method becomes operationalised And can’t do (yet) You don’t see the fish! No assessment of age, size, condition or health of the fish Relative abundance only, not absolute Can we accommodate these? Development of ecological assessment systems that don’t require knowledge of age- and size-structure? Or absolute abundance? - Use eDNA metabarcoding to complement and augment other methods Thanks to…
Bernd Hänfling Lori Lawson-Handley Kerry Walsh Ian Winfield Jianlong-Li Cristina de Muri
… and many others from partner organisations